code: def test_nccl_sparse_push_single_remainder():
      torch.cuda.set_device("cuda:0")
      dist.init_process_group(
          backend="nccl",
          init_method="tcp://127.0.0.1:12345",
          world_size=1,
          rank=0,
      )
  
      index = F.randint([10000], F.int32, F.ctx(), 0, 10000)
      value = F.uniform([10000, 100], F.float32, F.ctx(), -1.0, 1.0)
  
      part = NDArrayPartition(10000, 1, "remainder")
  
      ri, rv = nccl.sparse_all_to_all_push(index, value, part)
      assert F.array_equal(ri, index)
      assert F.array_equal(rv, value)
  
      dist.destroy_process_group()
  
file_path: dgl/tests/python/pytorch/cuda/test_nccl.py
imports: import unittest
  import backend
  import torch
  import torch.distributed
  from dgl.cuda import nccl
  from dgl.partition import NDArrayPartition
label_desc: Use image node_id 1 for calling a global function with example usage: test_nccl_sparse_push_single_remainder() without return types